Random Forest Calibration Strategy
Statisticalscore 6found Jul 22, 2026github.com/BallesJr/polymarket-edge-model
Systematic trading pipeline using Random Forest models to calibrate probabilities and detect mispricing on Polymarket.
This strategy employs a Random Forest calibration model to predict accurate outcome probabilities on Polymarket events. The pipeline includes backtesting, automated paper trading, and live execution. Entry occurs when the model's probability diverges from market odds by a calibrated threshold. Exits are based on convergence or time decay. Verified via BallesJr/polymarket-edge-model repository with Python implementation and recent commits. Requires ongoing model retraining and faces overfitting risks in rapidly changing markets.